Member of Technical Staff
Pubblicato il 13-10-2026 - servescale.ai in Milano
Company Descriptionis an economics-first, topology-aware AI inference platform that helps enterprises efficiently map models to the right infrastructure. By focusing on cost optimization and performance, the platform enables CIO organizations to deliver AI as a service to internal business and application teams. provides a unified, platform-centric approach that simplifies deployment, scaling, and management of AI workloads across diverse environments. The company is driven by a mission to make enterprise AI more reliable, efficient, and accessible, offering opportunities to work on cutting-edge infrastructure and AI technologies.
L'esperienza richiesta ai candidati, così come le competenze e le qualifiche aggiuntive necessarie per questo lavoro, sono elencate di seguito.
Role DescriptionAs a Member of Technical Staff at , you will design, build, and maintain core components of our AI inference platform, with an emphasis on scalability, reliability, and cost efficiency. You will collaborate with product, infrastructure, and data teams to architect solutions that optimize model placement, resource utilization, and performance across cloud and on-prem environments. Typical responsibilities include implementing backend services and APIs, improving system observability, participating in code reviews, and contributing to technical design discussions and documentation.
You will also help troubleshoot production issues, refine deployment pipelines,
and support new feature rollouts for enterprise customers. This is a full-time, remote role with cross-functional collaboration across time zones.
Qualifications (Not All Required, but The More The Better)
- Desire to experiment with Artificial Intelligence in the Software Development process; openness to using AI tools, such as CODEX or Claude Code to support and enhance the development process.
- Strong software engineering skills in languages such as Python, Go, or Java, with experience building distributed systems or platform services.
- Knowledge of cloud infrastructure (e.g., AWS, GCP, Azure), containers (Docker), and orchestration frameworks (Kubernetes) for deploying and scaling services.
- Familiarity with machine learning or AI workloads, model serving frameworks, and performance optimization for inference pipelines.
- Experience with monitoring, logging, and observability tools, as well as troubleshooting and performance tuning in production environments.
- Proficiency with CI/CD practices, version control (Git), and automated testing to ensure reliable and maintainable code.
- Comfort working in remote, collaborative teams, with clear communication, documentation, and ownership of technical deliverables.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience. xkiyazw
- Background in enterprise platforms, infrastructure-as-a-service, or AI platform engineering is a plus.